Biogeography-based optimisation

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)

Abstract

Biogeography-Based Optimisation (BBO) [1] is one of the recent evolutionary algorithms with successful application in a diverse field of studies. Similarly to other evolutionary algorithms, BBO has been equipped with crossover and mutations. The main difference between this algorithm and GA is the use of two operators to perform crossover and exploitation. The concepts of mutation is also similar, in which small changes occur in variables of solutions. However, each solution in BBO faces different mutation rates depending on its fitness, which makes it different from the GA algorithm. In this chapter, the inspiration and mathematical equations of the BBO algorithm are first given. A set of problems is then solved with this algorithm to observe and analyse its performance.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages57-72
Number of pages16
DOIs
Publication statusPublished - 1 Jan 2019
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume780
ISSN (Print)1860-949X

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Cite this

Mirjalili, S. (2019). Biogeography-based optimisation. In Studies in Computational Intelligence (pp. 57-72). (Studies in Computational Intelligence; Vol. 780). Springer Verlag. https://doi.org/10.1007/978-3-319-93025-1_5